爬虫实战——麻省理工学院新闻

发现宝藏

前些天发现了一个巨牛的人工智能学习网站，通俗易懂，风趣幽默，忍不住分享一下给大家。【宝藏入口】。

一、 目标

爬取news.mit.edu的字段,包含标题、内容，作者，发布时间，链接地址，文章快照 (可能需要翻墙才能访问)

二、 浅析

1.全部新闻大致分为4个模块

2.每个模块的标签列表大致如下

3.每个标签对应的文章列表大致如下

4.具体每篇文章对应的结构如下

三、获取所有模块

其实就四个模块，列举出来就好，然后对每个分别解析爬取每个模块

python">class MitnewsScraper:
    def __init__(self, root_url, model_url, img_output_dir):
        self.root_url = root_url
        self.model_url = model_url
        self.img_output_dir = img_output_dir
        self.headers = {
            'Referer': 'https://news.mit.edu/',
            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) '
                          'Chrome/122.0.0.0 Safari/537.36',
            'Cookie': '替换成你自己的',
        }

        ...

def run():
    root_url = 'https://news.mit.edu/'
    model_urls = ['https://news.mit.edu/topic', 'https://news.mit.edu/clp',
                  'https://news.mit.edu/department', 'https://news.mit.edu/']
    output_dir = 'D:\imgs\mit-news'

    for model_url in model_urls:
        scraper = MitnewsScraper(root_url, model_url, output_dir)
        scraper.catalogue_all_pages()

四、请求处理模块、版面、文章

先处理一个模块（TOPICS）

1. 分析切换页面的参数传递

如图可知是get请求,需要传一个参数page

2. 获取共有多少页标签并遍历版面

实际上是获取所有的page参数，然后进行遍历获取所有的标签

 # 获取一个模块有多少版面
    def catalogue_all_pages(self):
        response = requests.get(self.model_url, headers=self.headers)
        soup = BeautifulSoup(response.text, 'html.parser')
        try:
            match = re.search(r'of (\d+) topics', soup.text)
            total_catalogues = int(match.group(1))
            total_pages = math.ceil(total_catalogues / 20)
            print('topics模块一共有' + match.group(1) + '个版面,' + str(total_pages) + '页数据')
            for page in range(0, total_pages):
                self.parse_catalogues(page)
                print(f"========Finished catalogues page {page + 1}========")
        except:
            self.parse_catalogues(0)

3.解析版面并保存版面信息

前三个模块的版面列表

第四个模块的版面列表

 # 解析版面列表里的版面
    def parse_catalogues(self, page):
        params = {'page': page}
        response = requests.get(self.model_url, params=params, headers=self.headers)
        if response.status_code == 200:
            soup = BeautifulSoup(response.text, 'html.parser')
            if self.root_url == self.model_url:
                catalogue_list = soup.find('div',
                                           'site-browse--re***mended-section site-browse--re***mended-section--schools')
                catalogues_list = catalogue_list.find_all('li')
            else:
                catalogue_list = soup.find('ul', 'page-vocabulary--views--list')
                catalogues_list = catalogue_list.find_all('li')

            for index, catalogue in enumerate(catalogues_list):
                # 操作时间
                date = datetime.now()
                # 版面标题
                catalogue_title = catalogue.find('a').get_text(strip=True)
                print('第' + str(index + 1) + '个版面标题为:' + catalogue_title)

                catalogue_href = catalogue.find('a').get('href')
                # 版面id
                catalogue_id = catalogue_href[1:]
                catalogue_url = self.root_url + catalogue_href
                print('第' + str(index + 1) + '个版面地址为:' + catalogue_url)

                # 根据版面url解析文章列表
                response = requests.get(catalogue_url, headers=self.headers)
                soup = BeautifulSoup(response.text, 'html.parser')
                match = re.search(r'of (\d+)', soup.text)
                # 查找一个版面有多少篇文章
                total_cards = int(match.group(1))
                total_pages = math.ceil(total_cards / 15)
                print(f'{catalogue_title}版面一共有{total_cards}篇文章,' + f'{total_pages}页数据')
                for page in range(0, total_pages):
                    self.parse_cards_list(page, catalogue_url, catalogue_id)
                    print(f"========Finished {catalogue_title} 版面 page {page + 1}========")

                # 连接 MongoDB 数据库服务器
                client = MongoClient('mongodb://localhost:27017/')
                # 创建或选择数据库
                db = client['mit-news']
                # 创建或选择集合
                catalogues_collection = db['catalogues']
                # 插入示例数据到 catalogues 集合
                catalogue_data = {
                    'id': catalogue_id,
                    'date': date,
                    'title': catalogue_title,
                    'url': catalogue_url,
                    'cardSize': total_cards
                }
                catalogues_collection.insert_one(catalogue_data)
            return True
        else:
            raise Exception(f"Failed to fetch page {page}. Status code: {response.status_code}")

4. 解析文章列表和文章

寻找冗余部分并删除，例如

 # 解析文章列表里的文章
    def parse_cards_list(self, page, url, catalogue_id):
        params = {'page': page}
        response = requests.get(url, params=params, headers=self.headers)
        if response.status_code == 200:
            soup = BeautifulSoup(response.text, 'html.parser')
            card_list = soup.find('div', 'page-term--views--list')
            cards_list = card_list.find_all('div', 'page-term--views--list-item')
            for index, card in enumerate(cards_list):
                # 对应的版面id
                catalogue_id = catalogue_id
                # 操作时间
                date = datetime.now()
                # 文章标题
                card_title = card.find('a', 'term-page--news-article--item--title--link').find('span').get_text(
                    strip=True)

                # 文章简介
                card_introduction = card.find('p', 'term-page--news-article--item--dek').find('span').get_text(
                    strip=True)
                # 文章更新时间
                publish_time = card.find('p', 'term-page--news-article--item--publication-date').find('time').get(
                    'datetime')
                updateTime = datetime.strptime(publish_time, '%Y-%m-%dT%H:%M:%SZ')
                # 文章地址
                temp_url = card.find('div', 'term-page--news-article--item--cover-image').find('a').get('href')
                url = 'https://news.mit.edu' + temp_url
                # 文章id
                pattern = r'(\w+(-\w+)*)-(\d+)'
                match = re.search(pattern, temp_url)
                card_id = str(match.group(0))
                card_response = requests.get(url, headers=self.headers)
                soup = BeautifulSoup(card_response.text, 'html.parser')
                # 原始htmldom结构
                html_title = soup.find('div', id='block-mit-page-title')
                html_content = soup.find('div', id='block-mit-content')

                # 合并标题和内容
                html_title.append(html_content)
                html_cut1 = soup.find('div', 'news-article--topics')
                html_cut2 = soup.find('div', 'news-article--archives')
                html_cut3 = soup.find('div', 'news-article--content--side-column')
                html_cut4 = soup.find('div', 'news-article--press-inquiries')
                html_cut5 = soup.find_all('div', 'visually-hidden')
                html_cut6 = soup.find('p', 'news-article--images-gallery--nav--inner')

                # 移除元素
                if html_cut1:
                    html_cut1.extract()
                if html_cut2:
                    html_cut2.extract()
                if html_cut3:
                    html_cut3.extract()
                if html_cut4:
                    html_cut4.extract()
                if html_cut5:
                    for item in html_cut5:
                        item.extract()
                if html_cut6:
                    html_cut6.extract()
                # 获取合并后的内容文本
                html_content = html_title
                # 文章作者
                author_list = html_content.find('div', 'news-article--authored-by').find_all('span')
                author = ''
                for item in author_list:
                    author = author + item.get_text()
                # 增加保留html样式的源文本
                origin_html = html_content.prettify()  # String
                # 转义网页中的图片标签
                str_html = self.transcoding_tags(origin_html)
                # 再包装成
                temp_soup = BeautifulSoup(str_html, 'html.parser')
                # 反转译文件中的插图
                str_html = self.translate_tags(temp_soup.text)
                # 绑定更新内容
                content = self.clean_content(str_html)
                # 下载图片
                imgs = []
                img_array = soup.find_all('div', 'news-article--image-item')
                for item in img_array:
                    img_url = self.root_url + item.find('img').get('data-src')
                    imgs.append(img_url)
                if len(imgs) != 0:
                    # 下载图片
                    illustrations = self.download_images(imgs, card_id)
                # 连接 MongoDB 数据库服务器
                client = MongoClient('mongodb://localhost:27017/')
                # 创建或选择数据库
                db = client['mit-news']
                # 创建或选择集合
                cards_collection = db['cards']
                # 插入示例数据到 catalogues 集合
                card_data = {
                    'id': card_id,
                    'catalogueId': catalogue_id,
                    'type': 'mit-news',
                    'date': date,
                    'title': card_title,
                    'author': author,
                    'card_introduction': card_introduction,
                    'updatetime': updateTime,
                    'url': url,
                    'html_content': str(html_content),
                    'content': content,
                    'illustrations': illustrations,
                }
                cards_collection.insert_one(card_data)

            return True
        else:
            raise Exception(f"Failed to fetch page {page}. Status code: {response.status_code}")

5. 清洗文章

 # 工具 转义标签
    def transcoding_tags(self, htmlstr):
        re_img = re.***pile(r'\s*<(img.*?)>\s*', re.M)
        s = re_img.sub(r'\n @@##\1##@@ \n', htmlstr)  # IMG 转义
        return s

    # 工具 转义标签
    def translate_tags(self, htmlstr):
        re_img = re.***pile(r'@@##(img.*?)##@@', re.M)
        s = re_img.sub(r'<\1>', htmlstr)  # IMG 转义
        return s

    # 清洗文章
    def clean_content(self, content):
        if content is not None:
            content = re.sub(r'\r', r'\n', content)
            content = re.sub(r'\n{2,}', '', content)
            content = re.sub(r' {6,}', '', content)
            content = re.sub(r' {3,}\n', '', content)
            content = re.sub(r'<img src="../../../image/zxbl.gif"/>', '', content)
            content = content.replace(
                '<img border="0" src="****处理标记：[Article]时， 字段 [SnapUrl] 在数据源中没有找到! ****"/> ', '')
            content = content.replace(
                ''' <!--/enpcontent<INPUT type=checkbox value=0 name=titlecheckbox sourceid="<Source>SourcePh " style="display:none">''',
                '') \
                .replace(' <!--enpcontent', '').replace('<TABLE>', '')
            content = content.replace('<P>', '').replace('<\P>', '').replace('&nbsp;', ' ')
        return content

6. 保存文章图片

# 下载图片
    def download_images(self, img_urls, card_id):
        # 根据card_id创建一个新的子目录
        images_dir = os.path.join(self.img_output_dir, card_id)
        if not os.path.exists(images_dir):
            os.makedirs(images_dir)
            downloaded_images = []
            for index, img_url in enumerate(img_urls):
                try:
                    response = requests.get(img_url, stream=True, headers=self.headers)
                    if response.status_code == 200:
                        # 从URL中提取图片文件名
                        img_name_with_extension = img_url.split('/')[-1]
                        pattern = r'^[^?]*'
                        match = re.search(pattern, img_name_with_extension)
                        img_name = match.group(0)

                        # 保存图片
                        with open(os.path.join(images_dir, img_name), 'wb') as f:
                            f.write(response.content)
                        downloaded_images.append([img_url, os.path.join(images_dir, img_name)])
                except requests.exceptions.RequestException as e:
                    print(f'请求图片时发生错误：{e}')
                except Exception as e:
                    print(f'保存图片时发生错误：{e}')
            return downloaded_images
        # 如果文件夹存在则跳过
        else:
            print(f'文章id为{card_id}的图片文件夹已经存在')
            return []

五、完整代码

import os
from datetime import datetime
import requests
from bs4 import BeautifulSoup
from pymongo import MongoClient
import re
import math

class MitnewsScraper:
    def __init__(self, root_url, model_url, img_output_dir):
        self.root_url = root_url
        self.model_url = model_url
        self.img_output_dir = img_output_dir
        self.headers = {
            'Referer': 'https://news.mit.edu/',
            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) '
                          'Chrome/122.0.0.0 Safari/537.36',
            'Cookie': '替换成你自己的'
        }

    # 获取一个模块有多少版面
    def catalogue_all_pages(self):
        response = requests.get(self.model_url, headers=self.headers)
        soup = BeautifulSoup(response.text, 'html.parser')
        try:
            match = re.search(r'of (\d+) topics', soup.text)
            total_catalogues = int(match.group(1))
            total_pages = math.ceil(total_catalogues / 20)
            print('topics模块一共有' + match.group(1) + '个版面,' + str(total_pages) + '页数据')
            for page in range(0, total_pages):
                self.parse_catalogues(page)
                print(f"========Finished catalogues page {page + 1}========")
        except:
            self.parse_catalogues(0)

    # 解析版面列表里的版面
    def parse_catalogues(self, page):
        params = {'page': page}
        response = requests.get(self.model_url, params=params, headers=self.headers)
        if response.status_code == 200:
            soup = BeautifulSoup(response.text, 'html.parser')
            if self.root_url == self.model_url:
                catalogue_list = soup.find('div',
                                           'site-browse--re***mended-section site-browse--re***mended-section--schools')
                catalogues_list = catalogue_list.find_all('li')
            else:
                catalogue_list = soup.find('ul', 'page-vocabulary--views--list')
                catalogues_list = catalogue_list.find_all('li')

            for index, catalogue in enumerate(catalogues_list):
                # 操作时间
                date = datetime.now()
                # 版面标题
                catalogue_title = catalogue.find('a').get_text(strip=True)
                print('第' + str(index + 1) + '个版面标题为:' + catalogue_title)

                catalogue_href = catalogue.find('a').get('href')
                # 版面id
                catalogue_id = catalogue_href[1:]
                catalogue_url = self.root_url + catalogue_href
                print('第' + str(index + 1) + '个版面地址为:' + catalogue_url)

                # 根据版面url解析文章列表
                response = requests.get(catalogue_url, headers=self.headers)
                soup = BeautifulSoup(response.text, 'html.parser')
                match = re.search(r'of (\d+)', soup.text)
                # 查找一个版面有多少篇文章
                total_cards = int(match.group(1))
                total_pages = math.ceil(total_cards / 15)
                print(f'{catalogue_title}版面一共有{total_cards}篇文章,' + f'{total_pages}页数据')
                for page in range(0, total_pages):
                    self.parse_cards_list(page, catalogue_url, catalogue_id)
                    print(f"========Finished {catalogue_title} 版面 page {page + 1}========")

                # 连接 MongoDB 数据库服务器
                client = MongoClient('mongodb://localhost:27017/')
                # 创建或选择数据库
                db = client['mit-news']
                # 创建或选择集合
                catalogues_collection = db['catalogues']
                # 插入示例数据到 catalogues 集合
                catalogue_data = {
                    'id': catalogue_id,
                    'date': date,
                    'title': catalogue_title,
                    'url': catalogue_url,
                    'cardSize': total_cards
                }
                catalogues_collection.insert_one(catalogue_data)
            return True
        else:
            raise Exception(f"Failed to fetch page {page}. Status code: {response.status_code}")

    # 解析文章列表里的文章
    def parse_cards_list(self, page, url, catalogue_id):
        params = {'page': page}
        response = requests.get(url, params=params, headers=self.headers)
        if response.status_code == 200:
            soup = BeautifulSoup(response.text, 'html.parser')
            card_list = soup.find('div', 'page-term--views--list')
            cards_list = card_list.find_all('div', 'page-term--views--list-item')
            for index, card in enumerate(cards_list):
                # 对应的版面id
                catalogue_id = catalogue_id
                # 操作时间
                date = datetime.now()
                # 文章标题
                card_title = card.find('a', 'term-page--news-article--item--title--link').find('span').get_text(
                    strip=True)

                # 文章简介
                card_introduction = card.find('p', 'term-page--news-article--item--dek').find('span').get_text(
                    strip=True)
                # 文章更新时间
                publish_time = card.find('p', 'term-page--news-article--item--publication-date').find('time').get(
                    'datetime')
                updateTime = datetime.strptime(publish_time, '%Y-%m-%dT%H:%M:%SZ')
                # 文章地址
                temp_url = card.find('div', 'term-page--news-article--item--cover-image').find('a').get('href')
                url = 'https://news.mit.edu' + temp_url
                # 文章id
                pattern = r'(\w+(-\w+)*)-(\d+)'
                match = re.search(pattern, temp_url)
                card_id = str(match.group(0))
                card_response = requests.get(url, headers=self.headers)
                soup = BeautifulSoup(card_response.text, 'html.parser')
                # 原始htmldom结构
                html_title = soup.find('div', id='block-mit-page-title')
                html_content = soup.find('div', id='block-mit-content')

                # 合并标题和内容
                html_title.append(html_content)
                html_cut1 = soup.find('div', 'news-article--topics')
                html_cut2 = soup.find('div', 'news-article--archives')
                html_cut3 = soup.find('div', 'news-article--content--side-column')
                html_cut4 = soup.find('div', 'news-article--press-inquiries')
                html_cut5 = soup.find_all('div', 'visually-hidden')
                html_cut6 = soup.find('p', 'news-article--images-gallery--nav--inner')

                # 移除元素
                if html_cut1:
                    html_cut1.extract()
                if html_cut2:
                    html_cut2.extract()
                if html_cut3:
                    html_cut3.extract()
                if html_cut4:
                    html_cut4.extract()
                if html_cut5:
                    for item in html_cut5:
                        item.extract()
                if html_cut6:
                    html_cut6.extract()
                # 获取合并后的内容文本
                html_content = html_title
                # 文章作者
                author_list = html_content.find('div', 'news-article--authored-by').find_all('span')
                author = ''
                for item in author_list:
                    author = author + item.get_text()
                # 增加保留html样式的源文本
                origin_html = html_content.prettify()  # String
                # 转义网页中的图片标签
                str_html = self.transcoding_tags(origin_html)
                # 再包装成
                temp_soup = BeautifulSoup(str_html, 'html.parser')
                # 反转译文件中的插图
                str_html = self.translate_tags(temp_soup.text)
                # 绑定更新内容
                content = self.clean_content(str_html)
                # 下载图片
                imgs = []
                img_array = soup.find_all('div', 'news-article--image-item')
                for item in img_array:
                    img_url = self.root_url + item.find('img').get('data-src')
                    imgs.append(img_url)
                if len(imgs) != 0:
                    # 下载图片
                    illustrations = self.download_images(imgs, card_id)
                # 连接 MongoDB 数据库服务器
                client = MongoClient('mongodb://localhost:27017/')
                # 创建或选择数据库
                db = client['mit-news']
                # 创建或选择集合
                cards_collection = db['cards']
                # 插入示例数据到 catalogues 集合
                card_data = {
                    'id': card_id,
                    'catalogueId': catalogue_id,
                    'type': 'mit-news',
                    'date': date,
                    'title': card_title,
                    'author': author,
                    'card_introduction': card_introduction,
                    'updatetime': updateTime,
                    'url': url,
                    'html_content': str(html_content),
                    'content': content,
                    'illustrations': illustrations,
                }
                cards_collection.insert_one(card_data)

            return True
        else:
            raise Exception(f"Failed to fetch page {page}. Status code: {response.status_code}")

    # 下载图片
    def download_images(self, img_urls, card_id):
        # 根据card_id创建一个新的子目录
        images_dir = os.path.join(self.img_output_dir, card_id)
        if not os.path.exists(images_dir):
            os.makedirs(images_dir)
            downloaded_images = []
            for index, img_url in enumerate(img_urls):
                try:
                    response = requests.get(img_url, stream=True, headers=self.headers)
                    if response.status_code == 200:
                        # 从URL中提取图片文件名
                        img_name_with_extension = img_url.split('/')[-1]
                        pattern = r'^[^?]*'
                        match = re.search(pattern, img_name_with_extension)
                        img_name = match.group(0)

                        # 保存图片
                        with open(os.path.join(images_dir, img_name), 'wb') as f:
                            f.write(response.content)
                        downloaded_images.append([img_url, os.path.join(images_dir, img_name)])
                except requests.exceptions.RequestException as e:
                    print(f'请求图片时发生错误：{e}')
                except Exception as e:
                    print(f'保存图片时发生错误：{e}')
            return downloaded_images
        # 如果文件夹存在则跳过
        else:
            print(f'文章id为{card_id}的图片文件夹已经存在')
            return []

    # 工具 转义标签
    def transcoding_tags(self, htmlstr):
        re_img = re.***pile(r'\s*<(img.*?)>\s*', re.M)
        s = re_img.sub(r'\n @@##\1##@@ \n', htmlstr)  # IMG 转义
        return s

    # 工具 转义标签
    def translate_tags(self, htmlstr):
        re_img = re.***pile(r'@@##(img.*?)##@@', re.M)
        s = re_img.sub(r'<\1>', htmlstr)  # IMG 转义
        return s

    # 清洗文章
    def clean_content(self, content):
        if content is not None:
            content = re.sub(r'\r', r'\n', content)
            content = re.sub(r'\n{2,}', '', content)
            content = re.sub(r' {6,}', '', content)
            content = re.sub(r' {3,}\n', '', content)
            content = re.sub(r'<img src="../../../image/zxbl.gif"/>', '', content)
            content = content.replace(
                '<img border="0" src="****处理标记：[Article]时， 字段 [SnapUrl] 在数据源中没有找到! ****"/> ', '')
            content = content.replace(
                ''' <!--/enpcontent<INPUT type=checkbox value=0 name=titlecheckbox sourceid="<Source>SourcePh " style="display:none">''',
                '') \
                .replace(' <!--enpcontent', '').replace('<TABLE>', '')
            content = content.replace('<P>', '').replace('<\P>', '').replace('&nbsp;', ' ')
        return content

def run():
    root_url = 'https://news.mit.edu/'
    model_urls = ['https://news.mit.edu/topic', 'https://news.mit.edu/clp',
                  'https://news.mit.edu/department', 'https://news.mit.edu/']
    output_dir = 'D:\imgs\mit-news'

    for model_url in model_urls:
        scraper = MitnewsScraper(root_url, model_url, output_dir)
        scraper.catalogue_all_pages()

if __name__ == "__main__":
    run()

六、效果展示